(599al) An Optimization Strategy for Batch Process Scheduling Under Processing Time Uncertainty

Various events can occur during the operation of processes. Process scheduling thus should reflect the presence of such uncertainty while seeking for maximizing the performance in terms of economics and process stability.  There are many areas scheduling can make its impact including short term, medium term and long term horizon of interest. While short term scheduling is similar to control of specific process and long term scheduling is more associated with planning problem, medium term scheduling should take into account both factors. In this paper, scheduling problem of batch processes with parallel units is considered. We aim to allocate units for serial multiproduct multistage scheduling problem.

In order to take into account the processing time uncertainty, the concept of buffer is introduced to represent the complex processing time uncertainty. The resulting scheduling model is constructed using State-Task-Network (STN) representation. For the sake of computing the solution of such challenging problem, several techniques have been developed in this paper such as decomposing the overall problem into subproblems, simultaneously considering mass balance and time duration. The concept of complex task is proposed in this paper reflecting input, output state, conversion factor, batch size, processing time, cycle time and combination of available units.

Numerical examples with computational statistics have been presented with some remarks to illustrate the applicability of the proposed modeling methodology.